Proteogenomics and in silico structural and functional annotation of the barley powdery mildew Blumeria graminis f. sp. hordei

Blumeria graminis is an economically important obligate plant-pathogenic fungus, whose entire genome was recently sequenced and manually annotated using ab initio in silico predictions [7]. Employing large scale proteogenomic analysis we are now able to verify independently the existence of proteins predicted by 24% of open reading frame models. We compared the haustoria and sporulating hyphae proteomes and identified 71 proteins exclusively in haustoria, the feeding and effector-delivery organs of the pathogen. These proteins are ‘significantly smaller than the rest of the protein pool and predicted to be secreted. Most do not share any similarities with Swiss–Prot or Trembl entries nor possess any identifiable Pfam domains. We used a novel automated prediction pipeline to model the 3D structures of the proteins, identify putative ligand binding sites and predict regions of intrinsic disorder. This revealed that the protein set found exclusively in haustoria is significantly less disordered than the rest of the identified Blumeria proteins or random (and representative) protein sets generated from the yeast proteome. For most of the haustorial proteins with unknown functions no good templates could be found, from which to generate high quality models. Thus, these unknown proteins present potentially new protein folds that can be specific to the interaction of the pathogen with its host.

In silico identification and three-dimensional modelling of the missense mutation in ADAMTS2 in a sheep flock with dermatosparaxis

Background Dermatosparaxis (Ehlers–Danlos syndrome in humans) is characterized by extreme fragility of the skin. It is due to the lack of mature collagen caused by a failure in the enzymatic processing of procollagen I. We investigated the condition in a commercial sheep flock. Hypothesis/Objectives Mutations in the ADAM metallopeptidase with thrombospondin type 1 motif, 2 (ADAMTS2) locus, are involved in the development of dermatosparaxis in humans, cattle and the dorper sheep breed; consequently, this locus was investigated in the flock. Animals A single affected lamb, its dam, the dam of a second affected lamb and the rams in the flock were studied. Methods DNA was purified from blood, PCR primers were used to detect parts of the ADAMS2 gene and nucleotide sequencing was performed using Sanger's procedure. Skin samples were examined using standard histology procedures. Results A missense mutation was identified in the catalytic domain of ADAMTS2. The mutation is predicted to cause the substitution in the mature ADAMTS2 of a valine molecule by a methionine molecule (V15M) affecting the catalytic domain of the enzyme. Both the ‘sorting intolerant from tolerant’ (SIFT) and the PolyPhen-2 methodologies predicted a damaging effect for the mutation. Three-dimensional modelling suggested that this mutation may alter the stability of the protein folding or distort the structure, causing the protein to malfunction. Conclusions and clinical importance Detection of the mutation responsible for the pathology allowed us to remove the heterozygote ram, thus preventing additional cases in the flock.

In silico identification and characterization of protein-ligand binding sites

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.

Selection of candidate coding DNA barcoding regions for use on land plants

An in silico screen of 41 of the 81 coding regions of the Nicotiana plastid genome generated a shortlist of 12 candidates as DNA barcoding loci for land plants. These loci were evaluated for amplification and sequence variation against a reference set of 98 land plant taxa. The deployment of multiple primers and a modified multiplexed tandem polymerase chain reaction yielded 85–94% amplification across taxa, and mean sequence differences between sister taxa of 6.1 from 156 bases of accD to 22 from 493 bases of matK. We conclude that loci should be combined for effective diagnosis, and recommend further investigation of the following six loci: matK, rpoB, rpoC1, ndhJ, ycf5 and accD.

Detection of somaclonal variation during cocoa somatic embryogenesis characterised using cleaved amplified polymorphic sequence and the new freeware Artbio

The scarcity and stochastic nature of genetic mutations presents a significant challenge for scientists seeking to characterise de novo mutation frequency at specific loci. Such mutations can be particularly numerous during regeneration of plants from in vitro culture and can undermine the value of germplasm conservation efforts. We used cleaved amplified polymorphic sequence (CAPS) analysis to characterise new mutations amongst a clonal population of cocoa plants regenerated via a somatic embryogenesis protocol used previously for cocoa cryopreservation. Efficacy of the CAPS system for mutation detection was greatly improved after an ‘a priori’ in silico screen of reference target sequences for actual and potential restriction enzyme recognition sites using a new freely available software called Artbio. Artbio surveys known sequences for existing restriction enzyme recognition sites but also identifies all single nucleotide polymorphism (SNP) deviations from such motifs. Using this software, we performed an in silico screen of seven loci for restriction sites and their potential mutant SNP variants that were possible from 21 restriction enzymes. The four most informative locus-enzyme combinations were then used to survey the regenerant populations for de novo mutants. We characterised the pattern of point mutations and, using the outputs of Artbio, calculated the ratio of base substitution in 114 somatic embryo-derived cocoa regenerants originating from two explant genotypes. We found 49 polymorphisms, comprising 26.3% of the samples screened, with an inferred rate of 2.8 × 10−3 substitutions/screened base. This elevated rate is of a similar order of magnitude to previous reports of de novo microsatellite length mutations arising in the crop and suggests caution should be exercised when applying somatic embryogenesis for the conservation of plant germplasm.

Evaluation of the environmental specificity of fluorescence in situ hybridization (FISH) using fluorescence-activated cell sorting (FACS) of probe (PSE1284)-positive cells extracted from rhizosphere soil

We explicitly tested for the first time the ‘environmental specificity’ of traditional 16S rRNAtargeted fluorescence in situ hybridization (FISH) through comparison of the bacterial diversity actually targeted in the environment with the diversity that should be exactly targeted (i.e. without mismatches) according to in silico analysis. To do this, we exploited advances in modern Flow Cytometry that enabled improved detection and therefore sorting of sub-micron-sized particles and used probe PSE1284 (designed to target Pseudomonads) applied to Lolium perenne rhizosphere soil as our test system. The 6-carboxyfluorescein (6-FAM)-PSE1284-hybridised population, defined as displaying enhanced green fluorescence in Flow Cytometry, represented 3.51±1.28% of the total detected population when corrected using a nonsense (NON-EUB338) probe control. Analysis of 16S rRNA gene libraries constructed from Fluorescence Activated Cell Sorted (FACS) -recovered fluorescent populations (n=3), revealed that 98.5% (Pseudomonas spp. comprised 68.7% and Burkholderia spp. 29.8%) of the total sorted population was specifically targeted as evidenced by the homology of the 16S rRNA sequences to the probe sequence. In silico evaluation of probe PSE1284 with the use of RDP-10 probeMatch justified the existence of Burkholderia spp. among the sorted cells. The lack of novelty in Pseudomonas spp. sequences uncovered was notable, probably reflecting the well-studied nature of this functionally important genus. To judge the diversity recorded within the FACS-sorted population, rarefaction and DGGE analysis were used to evaluate, respectively, the proportion of Pseudomonas diversity uncovered by the sequencing effort and the representativeness of the Nycodenz® method for the extraction of bacterial cells from soil.

Analysis of protein networks in resting and collagen receptor (GPVI)-stimulated platelet sub-proteomes.

Proteomics approaches have made important contributions to the characterisation of platelet regulatory mechanisms. A common problem encountered with this method, however, is the masking of low-abundance (e.g. signalling) proteins in complex mixtures by highly abundant proteins. In this study, subcellular fractionation of washed human platelets either inactivated or stimulated with the glycoprotein (GP) VI collagen receptor agonist, collagen-related peptide, reduced the complexity of the platelet proteome. The majority of proteins identified by tandem mass spectrometry are involved in signalling. The effect of GPVI stimulation on levels of specific proteins in subcellular compartments was compared and analysed using in silico quantification, and protein associations were predicted using STRING (the search tool for recurring instances of neighbouring genes/proteins). Interestingly, we observed that some proteins that were previously unidentified in platelets including teneurin-1 and Van Gogh-like protein 1, translocated to the membrane upon GPVI stimulation. Newly identified proteins may be involved in GPVI signalling nodes of importance for haemostasis and thrombosis.

Genome scale reconstruction of a Salmonella metabolic model comparison of similarity and differences with a commensal Escherichia coli strain

Salmonella are closely related to commensal Escherichia coli but have gained virulence factors enabling them to behave as enteric pathogens. Less well studied are the similarities and differences that exist between the metabolic properties of these organisms that may contribute toward niche adaptation of Salmonella pathogens. To address this, we have constructed a genome scale Salmonella metabolic model (iMA945). The model comprises 945 open reading frames or genes, 1964 reactions, and 1036 metabolites. There was significant overlap with genes present in E. coli MG1655 model iAF1260. In silico growth predictions were simulated using the model on different carbon, nitrogen, phosphorous, and sulfur sources. These were compared with substrate utilization data gathered from high throughput phenotyping microarrays revealing good agreement. Of the compounds tested, the majority were utilizable by both Salmonella and E. coli. Nevertheless a number of differences were identified both between Salmonella and E. coli and also within the Salmonella strains included. These differences provide valuable insight into differences between a commensal and a closely related pathogen and within different pathogenic strains opening new avenues for future explorations.

Type III secretion homologs are present in Brucella melitensis, B-ovis, and B-suis biovars 1, 2, and 3

Protein sequences from characterized type III secretion (TTS) systems were used as probes in silico to identify several TTS gene homologs in the genome sequence of Brucella suis biovar 1 strain 1330. Four of the genes, named flhB, fliP, fliR, and fliF on the basis of greatest homologies to known flagellar apparatus proteins, were targeted in PCR and hybridization assays to determine their distribution among other Brucella nomen species and biovars. The results indicated that flhB, fliP, fliR and fliF are present in Brucella melitensis, Brucella ovis, and Brucella suis biovars 1, 2 and 3. Similar homologos have been reported previously in Brucella abortus. Using RT-PCR assays, we were unable to detect any expression of these genes. It is not yet known whether the genes are the cryptic remnants of a flagellar system or are actively involved in a process contributing to pathogenicity or previously undetected motility, but they are distributed widely in Brucella and merit further study to determine their role.

The role of prophage-like elements in the diversity of Salmonella enterica serovars

The Salmonella enterica serovar Typhi CT18 (S. Typhi) chromosome harbours seven distinct prophage-like elements, some of which may encode functional bacteriophages. In silico analyses were used to investigate these regions in S. Typhi CT18, and ultimately compare these integrated bacteriophages against 40 other Salmonella isolates using DNA microarray technology. S. Typhi CT18 contains prophages that show similarity to the lambda, Mu, P2 and P4 bacteriophage families. When compared to other S. Typhi isolates, these elements were generally conserved, supporting a clonal origin of this serovar. However, distinct variation was detected within a broad range of Salmonella serovars; many of the prophage regions are predicted to be specific to S. Typhi. Some of the P2 family prophage analysed have the potential to carry non-essential "cargo" genes within the hyper-variable tail region, an observation that suggests that these bacteriophage may confer a level of specialisation on their host. Lysogenic bacteriophages therefore play a crucial role in the generation of genetic diversity within S. enterica. (C) 2004 Elsevier Ltd. All rights reserved.

The integration of proteomics and systems approaches to map regulatory mechanisms underpinning platelet function.

Platelets in the circulation are triggered by vascular damage to activate, aggregate and form a thrombus that prevents excessive blood loss. Platelet activation is stringently regulated by intracellular signalling cascades, which when activated inappropriately lead to myocardial infarction and stroke. Strategies to address platelet dysfunction have included proteomics approaches which have lead to the discovery of a number of novel regulatory proteins of potential therapeutic value. Global analysis of platelet proteomes may enhance the outcome of these studies by arranging this information in a contextual manner that recapitulates established signalling complexes and predicts novel regulatory processes. Platelet signalling networks have already begun to be exploited with interrogation of protein datasets using in silico methodologies that locate functionally feasible protein clusters for subsequent biochemical validation. Characterization of these biological systems through analysis of spatial and temporal organization of component proteins is developing alongside advances in the proteomics field. This focused review highlights advances in platelet proteomics data mining approaches that complement the emerging systems biology field. We have also highlighted nucleated cell types as key examples that can inform platelet research. Therapeutic translation of these modern approaches to understanding platelet regulatory mechanisms will enable the development of novel anti-thrombotic strategies.

Evidence of neutral transcriptome evolution in plants

The transcriptome of an organism is its set of gene transcripts (mRNAs) at a defined spatial and temporal locus. Because gene expression is affected markedly by environmental and developmental perturbations, it is widely assumed that transcriptome divergence among taxa represents adaptive phenotypic selection. This assumption has been challenged by neutral theories which propose that stochastic processes drive transcriptome evolution. To test for evidence of neutral transcriptome evolution in plants, we quantified 18 494 gene transcripts in nonsenescent leaves of 14 taxa of Brassicaceae using robust cross-species transcriptomics which includes a two-step physical and in silico-based normalization procedure based on DNA similarity among taxa. Transcriptome divergence correlates positively with evolutionary distance between taxa and with variation in gene expression among samples. Results are similar for pseudogenes and chloroplast genes evolving at different rates. Remarkably, variation in transcript abundance among root-cell samples correlates positively with transcriptome divergence among root tissues and among taxa. Because neutral processes affect transcriptome evolution in plants, many differences in gene expression among or within taxa may be nonfunctional, reflecting ancestral plasticity and founder effects. Appropriate null models are required when comparing transcriptomes in space and time.

A comparison of the Thlaspi caerulescens and Thlaspi arvense shoot transcriptomes

Whole-genome transcriptome profiling is revealing how biological systems are regulated at the transcriptional level. This study reports the development of a robust method to profile and compare the transcriptomes of two nonmodel plant species, Thlaspi caerulescens, a zinc (Zn) hyperaccumulator, and Thlaspi arvense, a nonhyperaccumulator, using Affymetrix Arabidopsis thaliana ATH1-121501 GeneChip (R) arrays (Affymetrix, Santa Clara, CA, USA). Transcript abundance was quantified in the shoots of agar- and compost-grown plants of both species. Analyses were optimized using a genomic DNA (gDNA)-based probe-selection strategy based on the hybridization efficiency of Thlaspi gDNA with corresponding A. thaliana probes. In silico alignments of GeneChip (R) probes with Thlaspi gene sequences, and quantitative real-time PCR, confirmed the validity of this approach. Approximately 5000 genes were differentially expressed in the shoots of T. caerulescens compared with T. arvense, including genes involved in Zn transport and compartmentalization. Future functional analyses of genes identified as differentially expressed in the shoots of these closely related species will improve our understanding of the molecular mechanisms of Zn hyperaccumulation.

Rare variants in LRRK1 and Parkinson's disease

Approximately 20 % of individuals with Parkinson's disease (PD) report a positive family history. Yet, a large portion of causal and disease-modifying variants is still unknown. We used exome sequencing in two affected individuals from a family with late-onset PD to identify 15 potentially causal variants. Segregation analysis and frequency assessment in 862 PD cases and 1,014 ethnically matched controls highlighted variants in EEF1D and LRRK1 as the best candidates. Mutation screening of the coding regions of these genes in 862 cases and 1,014 controls revealed several novel non-synonymous variants in both genes in cases and controls. An in silico multi-model bioinformatics analysis was used to prioritize identified variants in LRRK1 for functional follow- up. However, protein expression, subcellular localization, and cell viability were not affected by the identified variants. Although it has yet to be proven conclusively that variants in LRRK1 are indeed causative of PD, our data strengthen a possible role for LRRK1 in addition to LRRK2 in the genetic underpinnings of PD but, at the same time, highlight the difficulties encountered in the study of rare variants identified by next-generation sequencing in diseases with autosomal dominant or complex patterns of inheritance.

The BioDICE Taverna plugin for clustering and visualization of biological data: a workflow for molecular compounds exploration

Background: In many experimental pipelines, clustering of multidimensional biological datasets is used to detect hidden structures in unlabelled input data. Taverna is a popular workflow management system that is used to design and execute scientific workflows and aid in silico experimentation. The availability of fast unsupervised methods for clustering and visualization in the Taverna platform is important to support a data-driven scientific discovery in complex and explorative bioinformatics applications. Results: This work presents a Taverna plugin, the Biological Data Interactive Clustering Explorer (BioDICE), that performs clustering of high-dimensional biological data and provides a nonlinear, topology preserving projection for the visualization of the input data and their similarities. The core algorithm in the BioDICE plugin is Fast Learning Self Organizing Map (FLSOM), which is an improved variant of the Self Organizing Map (SOM) algorithm. The plugin generates an interactive 2D map that allows the visual exploration of multidimensional data and the identification of groups of similar objects. The effectiveness of the plugin is demonstrated on a case study related to chemical compounds. Conclusions: The number and variety of available tools and its extensibility have made Taverna a popular choice for the development of scientific data workflows. This work presents a novel plugin, BioDICE, which adds a data-driven knowledge discovery component to Taverna. BioDICE provides an effective and powerful clustering tool, which can be adopted for the explorative analysis of biological datasets.